BioData World West 2017 agenda - day 1


BioData USA West: Day 1


Bringing big data and genomics to unlock cures for rare diseases

  • Connecting millions of data points to deliver ground breaking healthcare
  • Data is frozen knowledge. It's up to us to bring the heat to melt it
  • Investing in data

Augmenting Human Insights with AI in Life Science

  • Advanced analytics, machine learning and artificial intelligence (AI) have emerged as powerful tools in healthcare and life science.
  • Synthesizing diverse data is transforming the way we design experiments and investigate new therapies.
  • Exploring the power of AI technologies & its primary impact to augment human capabilities.

Elements of MVP (Million Veterans Project), where we want to go in the future, and our strategy to transform genomic efforts into the clinic.

  • Building one of the world's largest medical databases by safely collecting blood samples and health information from one million Veteran volunteers.
  • How to manipulate one of the largest genomic data sets in the world
  • Future use of MVP data to enhance the health of veterans

Speed networking and morning refreshments







Genomics and Health

Facilitating a culture of responsible and effective sharing of genome data

  • Every disease is a rare disease at the molecular level
  • Researchers will not have access to enough molecular test results for any rare disease without international data sharing
  • Those of us involved in the Global Alliance for Genomics and Health are building successful mechanisms for international data sharing
Precision Medicine

Genome Asia, sequencing 100,000 genomes across the Asian population

  • Despite being >40% of the world’s population - are significantly underrepresented in current genomic studies and reference genome databases even though the unique genetic diversity prevalent in South and East Asia provides a valuable source of clinical insights
  • Developing a commitment to open information
  • Understand biology of disease and enable new therapeutic options which will have global impact.
Artificial Intelligence

Drug design at genomic scale

  • We're remapping the entire chemical space of pharmaceuticals over the full human proteom.
  • A conversion matrix that will be the foundation of new predictive and design models for highly selective, new therapeutics, and a new view on the biology of those
Artificial Intelligence

PANEL DISCUSSION: What problems in the drug discovery/development arena is most ripe for the application of AI/ML to have a large impact?

  • What would a first rate approach to this problem look like in terms of the data, computing resources, machine learning algorithms, and domain knowledge needed?
  • What is the best way to build out an AI/ML capability in a way that could tackle not only this problem but the variety of future opportunities that are coming?
Dan Holder, Exec Dir, Biostatistics, Merck
Matthew Tudor, Principal Scientist, Chemistry, Informatics, Merck
Devan Mehrotra, Assoc. Vice President, Biostatistics, Merck Research Laboratories
Carol Rohl, Exec. Dir, IT Account Management, Scientific Information Management, Merck
Mathai Mammen, Senior Vice President of Cardiovascular Diseases, Metabolic diseases, Immunology and Oncology, Merck
Genomics and Health


  • VP Informatics, IlluminaEx CIOScott Kahn,
  • Jennifer Hall, President, American Heart Association
  • Chris Riley,Research Mgr - Institute for Precision CV Medicine, American Heart Association
  • Patrick Wayte,SVP, Center for Health Technology & Innovation, American Heart Association
  • Nicholas Marko, Founding board member of the International Society for Chief Data Officers, Director of Neurosurgical Oncology, Geisinger Health System
  • Pablo Roman-Garcia, Industry Officer, ELIXIR
    Scott Marshall Brandon, Executive Director, OpenMed Access
Precision Medicine


  • Christina Waters, CEO, RARE
  • David Smith, Professor of Laboratory Medicine and Pathology Chairman of the Technology Assessment Group Center for
  • Catherine Brownstein, Scientific Director, Manton Center for Orphan Disease Research
  • Daniel Jones, Professor and Vice Chair, Division of the Molecular Pathology, Ohio State University Comprehensive Cancer Center
  • Nikole Kimes, Senior Manager of Drug Safety and Public Health, Gilead Sciences
  • Jeffrey Bhasin, Clinical Epigenomics Leader, Cleveland Clinic
  • Manuel Corpas, Scientific Lead, Repositive
  • Fiona Nielson, CEO, DNA Digest, CEO, Repositive
Artificial Intelligence


  • Thomas Clozel, co-founder, OWKIN
  • Mark A. DePristo, Head of deep learning for genetics and genomics, Google Inc
  • Philip Nelson, Director, Software Engineering, Google Inc
  • Alex Zhavoronkov, (CSO, The Biogerontology Research Foundation) CEO, InSilico Medicine Inc

Networking Lunch

Genomics and Health

Uniting the translational and clinical research communities by developing an integrated i2b2/tranSMART platform in the cloud

  • Sharing clinical data on a grand scale
  • How to create a unilateral data sharing and collaborative system
  • The future of TranSMART
Precision Medicine

How to drive NGS into the clinic

  • What are the roadblocks to driving NGS into the clinic?
  • How systems are allowing for the provision of a personalized healthcare system
  • The greater picture
Artificial Intelligence

Artificial Intelligence in Drug Discovery and Aging Research

  • Insilicos Next generation mechanisms for drug development using Artificial Intelligence to discover new targets.
  • Breaking innovation stagnation in pharmaceuticals with AI
  • Working beyond human cognition and innovation using Insilco mechanisms
Genomics and Health

Genomics: Improving Scientific Insights from Clinical Trials

  • Advances in genome sequencing technologies have driven a dramatic increase in collecting genomics data, where genome sequencing in clinical trials is one of the fast growing applications.
  • Industry-wide pain points are slowing the streamlined integration of genomics data into clinical trials.
  • Clinical Trial Genomics provides at-scale, secure upload of genomics data and automated linking with study clinical data, machine-learning standardization of both data across studies, and turnkey analytics for immediately actionable hypotheses for on-going studies.
Precision Medicine

Oncology RWE, Hope, Dreams and Hard Realities

  • Big data has the potential to drive powerful insights in Cancer Care
  • Clinical trials enroll only 3% of cancer patients, we need to learn from every patient
  • Oncologists are seeking a “rapid learning system” that can democratize access to the most current clinical information.
Artificial Intelligence

Defeating aging through genomics

  • Effective antiaging methodologies through big data and genomics
  • Understanding systems using genome wide association studies to allude to new mechanisms to aging.
  • Treating aging as a disease
Genomics and Health

New advances in RNA-therapeutics bring RNA-seq into focus

  • New advances in RNA-therapeutics bring RNA-seq into focus
  • RNA therapeutics are innovative drugs to modulate the splicing and stability of specific RNA sequences
  • Envisagenics SpliceCoreTM is a cloud-based platform for the discovery of druggable splicing events
  • SpliceCore combines RNA-seq analysis with public data and machine learning to predict disease-causing splicing events and their regulators
Precision Medicine

An Innovative Approach to Improve Cancer Care Through Evidence-Based Technology: NCCN and FlatIron collaborate on NCCN Quality & Outcomes Database

  • Proving oncology stakeholders, the ability to garner critical insights needed to make informed decisions
  • Electronic health record (EHR) data aggregated for cancer quality and outcomes assessment
  • Leveraging cancer data in a meaningful way to identify opportunities to enhance and improve care
Artificial Intelligence

Software is Healing the World

  • Where do we need the most help?
  • Heart disease, cancer, diabetes
  • Where technology comes in
  • Cost of technology is exponentially decreasing, ushering in a new era in healthcare
  • Looking at current treatment methods and where tech comes into play for heart disease, cancer, and type II diabetes. With special focus on:
  • Heart disease: machine learning putting data to use
  • Cancer: early detection through deep learning
  • Type II diabetes: digital therapeutics
  • Creating big markets
  • Rethinking clinical tests, from population based to time based
  • Telemedicine
  • On demand medicine
  • Claims and interoperability
  • Implications
  • Software is ushering in a new era of prevention: (early) diagnostics, (wearable) instruments, (digital) therapies
  • 10-year outlook
Genomics and Health

New paradigms to enhance breast health through big data and genomics

  • Using Big Data and Genomics to understand Germline risks developing breast cancer and triage.
  • Breast cancer diagnosis and disease genomics for treatment and prognosis
Precision Medicine

PANEL DISCUSSION: Big Data is taking the guesswork out of medicine

  • How do you identify where to apply Big Data analytics in a Pharma company?
  • How can teams accelerate new insights and tap into data that is there, but not accessible today?
  • Can Big Data really change the way scientists, engineers and commercial teams support drug development?
  • How is running a big data project different from legacy data warehouses and business intelligence?
Genomics and Health

High Frequency Genomics: Direct-To-Patient studies power advances in monitoring disease activity & therapy response transcriptomics

  • The value of disease activity monitoring and therapy monitoring using blood-based transcriptomics
  • Challenges to making immune transcriptomics feasible
  • Using Direct-to-Patient sampling to drive larger cohorts of subjects
  • Key technologies to enable High-Frequency Transcriptomics

Afternoon Refreshments

Genomics and Health

FDA preparedness for “next gen sequencing”

  • IT/Bioinformatics tools developed at FDA to support research and regulatory needs
  • FDA research supporting regulatory evaluation of NGS data
  • FDA’s role in Precision Medicine Initiative
Precision Medicine

Enabling Pediatric Precision Genomics

  • Rare disease research in pediatrics requires collaborative networks
  • Networks need to enable institutions as well as investigators
  • Academic institutions benefit from enterprise genomic data and literacy strategies
Artificial Intelligence


15:50 Numerate
Brandon Allgood, CTO and a cofounder

16:05 Enlitic
Kevin Lyman, Chief Data Scientist

16:20 Lunit
Brandon Suh, Chief Medical Officer

16:35 Atomwise
Abraham Heifets, CEO

Genomics and Health

The Era of Big Genomics in Pharma

  • Therapeutic programs supported by human genetic evidence are 2x more likely to succeed
  • What pharma needs to be successful in scaling the application of genomics in discovery, development and diagnostics
  • De-siloing disparate data types to enable geno-pheno analysis and faster time to actionable insights
Precision Medicine

Big Data and Genomics: Empowering citizens to share health data through mobile technology

  • Who are the past, present, and future health data stakeholders?
  • What is the current state of health data sharing via mobile platforms?
  • In what ways do app-mediated research studies support citizen empowerment in research?
Genomics and Health

Integrative analysis, including genome-wide expression data, in Neuroblastoma

  • Linking genomic changes driving cancer to their consequences for biological processes
  • Testing predictive biomarkers based on gene expression
  • Development of predictive biomarkers using machine learning
Precision Medicine

A perspective for NGS based cancer diagnostics; assay development, validation and compliance in the midst of current and the future of Genomics

  • Clinical trials and research while focusing on enhancing cancer care delivery
  • Improving cancer outcomes through a targeted treatment approach
  • How we respond to findings through personalized, cancer-specific treatment plans.
Genomics and Health

How the cloud is affecting big data sharing?

  • Storing communicating and tracking your personal health records
  • Patient privacy and mechanisms
  • Data value and management with the patient at the center
Precision Medicine

The Joint Analysis of Many Matrices via ITeration (JAMMIT): Tailoring precise treatment strategies for cancer

  • High-dimensional data sets of measurements for different data types obtained from a common set of biosamples are proliferating at an exponential rate in public and private databases
  • The complexity of such “multi-modal” data has slowed the development of new predictive biomarkers and treatments for cancer
  • Sparse, rank-1 matrix approximations implemented by the JAMMIT algorithm provide a simple and powerful approach to extracting predictive signatures from multi-modal data
  • JAMMIT analysis of real experimental data for ovarian and liver cancer reveal connections between sparse signatures, immune checkpoint signaling, and overall survival
Gordon Okimoto, Co-Director, Biostatistics and Informatics, University of Hawaii Cancer Center
Artificial Intelligence

Supercomputing and the Future of Health

  • The use of AI in drug development
  • How BERG uses artificial intelligence to analyze tissue samples and clinical data to model and understand diseases and guide drug discovery
  • Understanding why AI is an overdue disruption to drive innovation and pharmaceutical development
Genomics and Health

Rare disease patient community engagement, the key to accelerate research to clinical impact, a case study

  • Focused generation and aggregation of rare disease "big data" can close the gap of time between research and clinical impact
  • empowering patient family communities as equal stakeholders can drive international collaboration and data sharing
  • leveraging genetics/functional genomics of one rare disease can be leveraged to rare and common diseases of similar biology
Precision Medicine

A practical approach to precision medicine education

  • Genomic literacy: Developing a minimalist curriculum for healthcare providers, i.e. teach me just what I need to know about genomics to practice precision medicine
  • Skills: Incorporating practical, hands on experiences ordering tests, interpreting reports, communicating with patients
  • Awareness: Providing opportunities to stay apprised of the latest applications of genomics in healthcare
Artificial Intelligence

Connecting tumor genomics with therapeutics through multi-dimensional network modules

  • Cancer cell lines can model therapeutic responses, but only partially reflect tumor biology.
  • Using MAGNETIC, a new method to integrate molecular profiling data using functional networks, we identify 219 gene modules in TCGA breast cancers that capture recurrent alterations, reveal new roles for H3K27 tri-methylation and accurately quantitate various cell types within the tumor microenvironment.
  • We show that a significant portion of gene expression and methylation in tumors is poorly reproduced in cell lines due to differences in biology and microenvironment and MAGNETIC identifies therapeutic biomarkers that are robust to these differences. This work addresses a fundamental challenge in pharmacogenomics that can only be overcome by the joint analysis of patient and cell line data

Evening cocktail reception


End of Day One